Datasets › DreamBooth
DreamBooth
The DreamBooth dataset is a collection of images used for fine-tuning text-to-image diffusion models for subject-driven generation¹. Here are some key details about the dataset:
- The dataset includes 30 subjects from 15 different classes¹.
- Among these subjects, 9 are live subjects (such as dogs and cats) and 21 are objects¹.
- The dataset contains a variable number of images per subject, typically between 4 to 6 images¹.
- Images of the subjects are usually captured in different conditions, environments, and under different angles¹.
- The dataset also includes a file
prompts_and_classes.txtwhich contains all of the prompts used in the paper for live subjects and objects, as well as the class name used for the subjects¹. - The images have either been captured by the paper authors or sourced from www.unsplash.com¹.
- The
references_and_licenses.txtfile contains a list of all the reference links to the images in www.unsplash.com, along with the attribution to the photographer and the license of the image¹.
This dataset is part of the official repository for the Google paper "DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation"¹. If you use this work, please cite the paper¹. Please note that this is not an officially supported Google product¹.
(1) GitHub - google/dreambooth. https://github.com/google/dreambooth. (2) DreamBooth - Hugging Face. https://huggingface.co/docs/diffusers/training/dreambooth. (3) google/dreambooth · Datasets at Hugging Face. https://huggingface.co/datasets/google/dreambooth. (4) dreambooth: Mirror of https://huggingface.co/datasets/google .... https://gitee.com/hf-datasets/dreambooth. (5) undefined. https://github.com/huggingface/diffusers. (6) undefined. https://huggingface.co/datasets/google.
Benchmarks archive 2025-07-28
All 1 leaderboard whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.
| First row (archive order) | Paper | Code | ||||
|---|---|---|---|---|---|---|
| Personalized Image Generation | DreamBooth | DreamBooth LoRA SDXL v1.0 Overall (CP * PF) 0.517 | DreamBooth: Fine Tuning Text-to-Image Diffusion Models... | PaddlePaddle/PaddleNLP +11 | 7 | Compare |
Papers archive 2025-07-28
5 shown of 5 papers with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 523. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.
| Date | Samples run Syntology | |||
|---|---|---|---|---|
| Generative Multimodal Models are In-Context Learners | 1 | 1 | 20 Dec 2023 | ran 3 of 4 samples (1 unverified) |
| IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models | 4 | 2 | 13 Aug 2023 | ran 3 of 8 samples (5 unverified) |
| BLIP-Diffusion: Pre-trained Subject Representation for Controllable Text-to-Image Generation and Editing | 1 | 1 | 24 May 2023 | not harvested |
| DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation | 12 | 2 | 25 Aug 2022 | ran 10 of 12 samples (2 unverified; 8 pointer-only for licence) |
| An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion | 9 | 1 | 2 Aug 2022 | ran 10 of 13 samples (3 unverified; 1 pointer-only for licence) |
Dataset loaders archive 2025-07-28
No loader listed in the archive.
Tasks archive 2025-07-28
License archive 2025-07-28
No licence recorded in the archive. Absence here is not a statement about the dataset's terms.
Modalities archive 2025-07-28
No modality tagged.
Languages archive 2025-07-28
No language tagged.
Variants archive 2025-07-28
- DreamBooth
1 variant name, as the archive lists them.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections